Zachary Depp, Halit Bugra Tulay, C. Emre Koksal (The Ohio State University)

The traditional vehicular roll-jam attack is an effective means to gain access to the target vehicle by jamming and recording key fob inputs from a victim. However, it requires specific knowledge of the attack surface, and delicate tuning of software-defined radio parameters. We have developed an enhanced version of the roll-jam attack that uses a known noise signal for jamming, in contrast to the additive white Gaussian noise that is typically used in the attack. Using a known noise signal allows for less strict tuning of the software-defined radios used in the attack, and allows for digital noise removal of the recorded input to enhance the replay attack.

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A Robust Counting Sketch for Data Plane Intrusion Detection

Sian Kim (Ewha Womans University), Changhun Jung (Ewha Womans University), RhongHo Jang (Wayne State University), David Mohaisen (University of Central Florida), DaeHun Nyang (Ewha Womans University)

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GPS Spoofing Attack Detection on Intersection Movement Assist using...

Jun Ying (Purdue University), Yiheng Feng (Purdue University), Qi Alfred Chen (University of California, Irvine), Z. Morley Mao (University of Michigan)

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Automatic Retrieval of Privacy Factors from IoMT Policies: ML...

Nyteisha Bookert, Mohd Anwar (North Carolina Agricultural and Technical State University)

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WIP: A First Look At Employing Large Multimodal Models...

Mohammed Aldeen, Pedram MohajerAnsari, Jin Ma, Mashrur Chowdhury, Long Cheng, Mert D. Pesé (Clemson University)

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